Society service is one components of Tri Dharma University in addition to education and research. With implementation of dharma service except two other dharma, expected there is an association between University and Society to anticipate University insulation from local society. Society service is manifested in the form of Development Family Empowerment Post (Posdaya) Mosque-Based.

As a form of student evaluation to Society service activities, required a system to evaluate and monitor Posdaya distribution from results of student work program. One of them is Posdaya classification based predicate ratings with indicators that have been determined. The classification results are intended to provide an overview Posdaya mosque-based implementation to stakeholders implementing these activities, so that action can be taken quickly when many found Posdaya poor implementation.

This study discusses Posdaya classification and mapping using Naïve Bayes Classifier method. Naïve Bayes Classifier is simple probabilistic-based prediction techniques based on the application of Bayes 'theorem (or Bayes' rule) with the assumption of independence (lack of dependence) is strong (naive). The classification is divided into three categories, with category good Posdaya, fairly good and less good. The aim is to classifying and mapping Posdaya as a form of student activities evaluation in Posdaya location and overview of Posdaya implementation.